Test drive Paradise

What is Machine Learning?

Coined in 1959 by Arthur Samuel, “Machine learning (ML) is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to “learn” (e.g., progressively improve performance on a specific task) from data, without being explicitly programmed.”

Reveal the attributes that correspond to a geobody according to their relative contribution through the SOM process

“…machine learning software in Paradise is applied to seismic attributes to find patterns and important geology… [and] Self-Organizing Maps are used to analyze data at single sample resolution.”

— American Oil & Gas Reporter

Guided ThoughtFlowsTM

Paradise enables every interpreter to use powerful machine learning processes through straight forward, left-to-right guided workflows. Learn more about how to set up and generate a PCA chart of attributes and SOM classification results, then use the unique 2D Colormap with the 3D Viewer to interpret geobodies.

“Paradise distills a variety of information from many attributes simultaneously at single sample resolution… This is one of the many differences in the application of machine learning and pattern recognition methods available in Paradise.”

— GEO ExPro

Read case studies on the application of machine learning processes, including Self-Organizing Maps (SOM’s) and Principal Component Analysis (PCA), as applied to seismic attributes in various geologic settings, including onshore – conventional and unconventional – and offshore.

What can we help you find today? What can we help you find today? More information about machine learningMore information about ParadiseMore information on attributesIdentifying DHIs using SOMIdentifying thin beds / interpreting below tuningIdentifying geobodies using SOMSomething else...Just looking around

Paradise Evaluation

Contact us to see for yourself how the machine learning capabilities in Paradise can reduce
exploration risk and field development cost through an evaluation of the software.